How does Big Data drive customer experience ?
7 best practices for companies to translate big data into actionable strategies.
June 13th, 2019 Big data
"You can't manage what you don't measure", one of the most important quotes in modern business attributed by Peter Drucker a widely regarded management thinker, author and philosopher of this subject and one of the greatest management consultants of our time.
It’s apparent that if you can’t measure business performance and know the results then you can't manage or grow the business any further. Specifically, businesses need to understand how “big data” will influence customer experience and so first we need to explain exactly what we mean by “big data”.
What is big data?
Big data is the collection and analysis of data in its rawest form but specifically, how data is processed and used as marketing leverage is also part of the practice of big data. For our purpose of doing business the New York Times describes big data as "shorthand for advancing trends in technology that open the door to a new approach to understanding the world and making decisions."
What does big data have to do with customer experience?
The information companies can cull from the massive amount of information big data collects can be used to offer your clients a better customer experience.
To uncover patterns, market trends, and customer preferences big data helps businesses to make informed predictions faster.
Every time you get a recommendation from a customer, you are experiencing big data in practice. Many organizations let shoppers know that they collect information about them as they shop and companies use this data to offer a better shopping experience, presenting more relevant items to you first and offering targeted promotions.
By consistently driving the right products and services to your customer, the more your customer loyalty increases.
Whilst big data is is the subject of some debate in regards to the boundaries of privacy and the collection of personal information, many consumers have adapted and understood why businesses need to anticipate their needs.
Why big data empowers the personalization of consumerism.
Big data empowers the personalization of consumerism because it can increase customer loyalty as well as reduce the number of returned products.
Big data engages businesses to target intended audience demographics in a refined way as well as improve multi-channel marketing efforts and be clear about what factors have the most impact on customer satisfaction metrics.
The importance of big data in a consumerist society means that every profit generating business is reliant upon finding the metrics that equate amplification in their number of customers and clients. Further to this, customer retention plays a significant role in the role of customer experience because only if the customer is happy will they remain loyal to a business. Big data helps to improve the customer experience because:
1. Big data helps companies to understand the customer's purchase history:
Thorough knowledge of a customer's past purchases allows companies to offer their best recommendations and suggestions according to the individual observations and this equates to an overall amplified and enjoyable purchasing experience.
2. Big Data analysis helps companies to easily Identify the behavioral patterns of the target audience:
Creating custom and personalized customer experiences stem from understanding the behavioral habits of your target audience. Data insights such as interests, demands and the customers' needs will assist your business in offering a better experience.
With leveraging big data, companies can understand their customers better and position themselves to curate much more powerful and effective campaigns.
The rise of Cross-Organizational knowledge transfer in data architects.
AI and big data is a crucial component of meeting the demands of scaled customer service this year - 2019. Over the last few years, it's become a common practice for companies to hire data scientists and these technology vendors have made big data more digestible to a wider set of professional. Along with the invaluable skill sets that data scientists provide, companies are also restructuring their teams so that a wider percentage of individuals can learn and leverage the technology and in turn become data specialists.
As more companies adopt AI and big data technologies, more in-house teams can connect the dots across the customer journey and impact the customer experience. The rise of cross-organizational knowledge transfer in data architects will empower the customer experience from the inside out and integrating and centralizing incoming data becomes manageable which inevitably improves customer satisfaction and loyalty in real time.
The rise of widespread big data adoption in the Retail Sector.
Over the last few years, many industries have really started to hone in on customer experience as a central and primary elevation tool. The prime example? Retail.
Brands are now seeking to understand more of what their customers value when they visit their stores or shop online, and this can range from convenience to the speed of the transactions, to the layout of the store. Rather than manually processing customer feedback, consumers now expect to have their customer experience quantified in real time.
Because big data and AI technology target the analytics of the consumer journey, retailers can now personalize and segment their marketing efforts and customer experience strategy. Access to this type of technology is powering trends that consumers are driven by such as checkout free retail, social commerce, pop up experiences and more.
Big data and digital transformation best practice.
"Big data seems to have a paralyzing effect on many companies," explains Deloitte for the Wall Street Journal. "As much as they may want to exploit it to improve decision-making or uncover ways to monetize it, many organizations' initial big data efforts flounder and fail to realize desired value."
Businesses often become enmeshed with technical concepts surrounding the practice of big data because many do not understand data sampling or the business fails to collect the correct pieces of data.
The shortcomings of understanding technical concepts make the data no more than guesswork and in this way, the information can negatively impact the business. This misunderstanding often impact businesses in the early stages of digital transformation as this is when business developers often realize how essential to proactivity big data will be.
Challenges occur when data is gathered for the sake of having it but not for the advantage of making improvements. Eventually, companies end up with huge amounts of incomprehensible data and this stifles the ability to produce innovative predictions.
Apart from being used extensively by the sales and marketing teams, big data is used by the customer service teams of the company and, big data consulting helps the companies to understand their customer and the target audience better.
7 best practices for companies to translate data into actionable strategies in 2019.
- Identify the single problem that they want to solve. What is your business goal? This may sound simple but ensure that you begin each initiative by clarifying your company’s specific goal for a particular effort.
- Assemble a team that understands your subject matter and the challenges of big data and that can assist you in selecting the correct components to measure and analyze it.
- As your business begins to accrue more data sets so will the time it takes to analyze and report back on them. Machine learning and artificial intelligence can lead to deeper data intelligence that is humanly possible to interpret.
- To gain value from data, data governance practices will ensure that the data used by your business is of the highest quality throughout its entire lifecycle. Centering on the availability of data, usability, integration, and security, data governance is an evolutionary process for new businesses that incorporate data management practices, as it allows for the entire industry to use the data.
- Whether you’re an SME, large business or a Fortune 500 company, it’s crucial to store your data securely and ensure that the data is used in good time to avoid it be ineffective.
- In any event, where you suspect a data breach, having a contingency plan with clear decision points will quickly direct you to any actions that are required by law, regulation, or good faith to disclose a potential or realized breach.
- Some organizations overlook process regarding the introduction of data classification and ownership, however, this should be an important and straightforward concept to launch into any business environment.
Whilst we can’t predict everything, we know that big data will continue making a huge impact on improving the customer experience in 2019 and beyond. With the capabilities to deduce data-driven insights, companies can keep up with evolving customer demands and behaviors.